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| data analytics for digital marketing: Big Data Analytics Kiran Chaudhary, Mansaf Alam, 2022-11-02 Big Data Analytics: Digital Marketing and Decision-Making covers the advances related to marketing and business analytics. Investment marketing analytics can create value through proper allocation of resources and resource orchestration processes. The use of data analytics tools can be used to improve and speed decision-making processes. Chapters examining analytics for decision-making cover such topics as: Big data analytics for gathering business intelligence Data analytics and consumer behavior The role of big data analytics in organizational decision-making This book also looks at digital marketing and focuses on such areas as: The prediction of marketing by consumer analytics Web analytics for digital marketing Smart retailing Leveraging web analytics for optimizing digital marketing strategies Big Data Analytics: Digital Marketing and Decision-Making aims to help organizations increase their profits by making better decisions on time through the use of data analytics. It is written for students, practitioners, industry professionals, researchers, and faculty working in the field of commerce and marketing, big data analytics, and organizational decision-making. |
| data analytics for digital marketing: Marketing Analytics Rajkumar Venkatesan, Paul W. Farris, Ronald T. Wilcox, 2021-01-13 The authors of the pioneering Cutting-Edge Marketing Analytics return to the vital conversation of leveraging big data with Marketing Analytics: Essential Tools for Data-Driven Decisions, which updates and expands on the earlier book as we enter the 2020s. As they illustrate, big data analytics is the engine that drives marketing, providing a forward-looking, predictive perspective for marketing decision-making. The book presents actual cases and data, giving readers invaluable real-world instruction. The cases show how to identify relevant data, choose the best analytics technique, and investigate the link between marketing plans and customer behavior. These actual scenarios shed light on the most pressing marketing questions, such as setting the optimal price for one’s product or designing effective digital marketing campaigns. Big data is currently the most powerful resource to the marketing professional, and this book illustrates how to fully harness that power to effectively maximize marketing efforts. |
| data analytics for digital marketing: Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing Singh, Amandeep, 2021-06-18 The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies. |
| data analytics for digital marketing: Digital Analytics for Marketing A. Karim Feroz, Gohar F. Khan, Marshall Sponder, 2024-01-25 This second edition of Digital Analytics for Marketing provides students with a comprehensive overview of the tools needed to measure digital activity and implement best practices when using data to inform marketing strategy. It is the first text of its kind to introduce students to analytics platforms from a practical marketing perspective. Demonstrating how to integrate large amounts of data from web, digital, social, and search platforms, this helpful guide offers actionable insights into data analysis, explaining how to connect the dots and humanize information to make effective marketing decisions. The authors cover timely topics, such as social media, web analytics, marketing analytics challenges, and dashboards, helping students to make sense of business measurement challenges, extract insights, and take effective actions. The book’s experiential approach, combined with chapter objectives, summaries, and review questions, will engage readers, deepening their learning by helping them to think outside the box. Filled with engaging, interactive exercises and interesting insights from industry experts, this book will appeal to undergraduate and postgraduate students of digital marketing, online marketing, and analytics. Online support materials for this book include an instructor’s manual, test bank, and PowerPoint slides. |
| data analytics for digital marketing: Techno-Social Systems for Modern Economical and Governmental Infrastructures Alexander Troussov, Sergey Maruev, 2018-12-14 This book covers theoretical and practical aspects of mining techno-social systems which have potential for the creation of scalable methods and applications for business, governance and economics. It also gives an overview of state of the art methods in mining big data-- |
| data analytics for digital marketing: Digital Marketing Analytics Kevin Hartman, 2020-09-15 From Kevin Hartman, Director of Analytics at Google, comes an essential guide for anyone seeking to collect, analyze, and visualize data in today's digital world (printed in black & white to keep print costs down). Even if you know nothing about digital marketing analytics, digital marketing analytics knows plenty about you. It's a fundamental, inescapable, and permanent cornerstone of modern business that affects the lives of analytics professionals and consumers in equal measure. This five-part book is an attempt to provide the context, perspective, and information needed to make analytics accessible to people who understand its reach and relevance and want to learn more. PART 1: The Day the Geeks Took Over The ubiquity of data analytics today isn't just a product of the past half-century's transformative and revolutionary changes in commerce and technology. Humanity has been developing, analyzing, and using data for millennia. Understanding where digital marketing analytics is now and where it will be in five, 10, or 50 years requires a holistic and historical view of our relationship and interaction with data. Part 1 looks at modern analysts and analytics in the context of its distinct historical epochs, each one containing major inflection points and laying a foundation for future advancements in the ART + SCIENCE that is modern data analytics. PART 2: Consumer/Brand Relationships The methods that brands use to build relationships with consumers - online video, search, display ads, and social media - give analysts a wealth of data about behaviors on these platforms. Knowing how to assess successful consumer/brand relationships and understanding a consumer's purchase journey requires a useable framework for parsing this data. In Part 2, we explore each digital channel in-depth, including a discussion of key metrics and measurements, how consumers interact with brands on each platform, and ways of organizing consumer data that enable actionable insights. PART 3: The Science of Analytics Part 3 focuses on understanding digital data creation, how brands use that data to measure digital marketing effectiveness, and the tools and skill sets analysts need to work effectively with data. While the contents are lightly technical, this section veers into the colloquial as we dive into multitouch attribution models, media mix models, incrementality studies, and other ways analysts conduct marketing measurement today. Part 3 also provides a useful framework for evaluating data analysis and visualization tools and explains the critical importance of digital marketing maturity to analysts and the companies for which they work. PART 4: The Art of Analytics Every analyst dreams of coming up with the Big Idea - the game-changing and previously unseen insight or approach that gives their organization a competitive advantage and their career a huge boost. But dreaming won't get you there. It requires a thoughtful and disciplined approach to analysis projects. In this part of the book, I detail the four elements of the Marketing Analytics Process (MAP): plan, collect, analyze, report. Part 4 also explains the role of the analyst, the six mutually exclusive and collectively exhaustive (MECE) marketing objectives, how to find context and patterns in collected data, and how to avoid the pitfalls of bias. PART 5: Storytelling with Data In Part 5, we dive headlong into the most important aspect of digital marketing analytics: transforming the data the analyst compiled into a comprehensive, coherent, and meaningful report. I outline the key characteristics of good visuals and the minutiae of chart design and provide a five-step process for analysts to follow when they're on their feet and presenting to an audience. |
| data analytics for digital marketing: Data-Driven Marketing Mark Jeffery, 2010-02-08 NAMED BEST MARKETING BOOK OF 2011 BY THE AMERICAN MARKETING ASSOCIATION How organizations can deliver significant performance gains through strategic investment in marketing In the new era of tight marketing budgets, no organization can continue to spend on marketing without knowing what's working and what's wasted. Data-driven marketing improves efficiency and effectiveness of marketing expenditures across the spectrum of marketing activities from branding and awareness, trail and loyalty, to new product launch and Internet marketing. Based on new research from the Kellogg School of Management, this book is a clear and convincing guide to using a more rigorous, data-driven strategic approach to deliver significant performance gains from your marketing. Explains how to use data-driven marketing to deliver return on marketing investment (ROMI) in any organization In-depth discussion of the fifteen key metrics every marketer should know Based on original research from America's leading marketing business school, complemented by experience teaching ROMI to executives at Microsoft, DuPont, Nisan, Philips, Sony and many other firms Uses data from a rigorous survey on strategic marketing performance management of 252 Fortune 1000 firms, capturing $53 billion of annual marketing spending In-depth examples of how to apply the principles in small and large organizations Free downloadable ROMI templates for all examples given in the book With every department under the microscope looking for results, those who properly use data to optimize their marketing are going to come out on top every time. |
| data analytics for digital marketing: Advanced Digital Marketing Strategies in a Data-Driven Era Saura, Jose Ramon, 2021-06-25 In the last decade, the use of data sciences in the digital marketing environment has increased. Digital marketing has transformed how companies communicate with their customers around the world. The increase in the use of social networks and how users communicate with companies on the internet has given rise to new business models based on the bidirectionality of communication between companies and internet users. Digital marketing, new business models, data-driven approaches, online advertising campaigns, and other digital strategies have gathered user opinions and comments through this new online channel. In this way, companies are beginning to see the digital ecosystem as not only the present but also the future. However, despite these advances, relevant evidence on the measures to improve the management of data sciences in digital marketing remains scarce. Advanced Digital Marketing Strategies in a Data-Driven Era contains high-quality research that presents a holistic overview of the main applications of data sciences to digital marketing and generates insights related to the creation of innovative data mining and knowledge discovery techniques applied to traditional and digital marketing strategies. The book analyzes how companies are adopting these new data-driven methods and how these strategies influence digital marketing. Discussing topics such as digital strategies, social media marketing, big data, marketing analytics, and data sciences, this book is essential for marketers, digital marketers, advertisers, brand managers, managers, executives, social media analysts, IT specialists, data scientists, students, researchers, and academicians in the field. |
| data analytics for digital marketing: Data Science for Marketing Analytics Mirza Rahim Baig, Gururajan Govindan, Vishwesh Ravi Shrimali, 2021-09-07 Turbocharge your marketing plans by making the leap from simple descriptive statistics in Excel to sophisticated predictive analytics with the Python programming language Key FeaturesUse data analytics and machine learning in a sales and marketing contextGain insights from data to make better business decisionsBuild your experience and confidence with realistic hands-on practiceBook Description Unleash the power of data to reach your marketing goals with this practical guide to data science for business. This book will help you get started on your journey to becoming a master of marketing analytics with Python. You'll work with relevant datasets and build your practical skills by tackling engaging exercises and activities that simulate real-world market analysis projects. You'll learn to think like a data scientist, build your problem-solving skills, and discover how to look at data in new ways to deliver business insights and make intelligent data-driven decisions. As well as learning how to clean, explore, and visualize data, you'll implement machine learning algorithms and build models to make predictions. As you work through the book, you'll use Python tools to analyze sales, visualize advertising data, predict revenue, address customer churn, and implement customer segmentation to understand behavior. By the end of this book, you'll have the knowledge, skills, and confidence to implement data science and machine learning techniques to better understand your marketing data and improve your decision-making. What you will learnLoad, clean, and explore sales and marketing data using pandasForm and test hypotheses using real data sets and analytics toolsVisualize patterns in customer behavior using MatplotlibUse advanced machine learning models like random forest and SVMUse various unsupervised learning algorithms for customer segmentationUse supervised learning techniques for sales predictionEvaluate and compare different models to get the best outcomesOptimize models with hyperparameter tuning and SMOTEWho this book is for This marketing book is for anyone who wants to learn how to use Python for cutting-edge marketing analytics. Whether you're a developer who wants to move into marketing, or a marketing analyst who wants to learn more sophisticated tools and techniques, this book will get you on the right path. Basic prior knowledge of Python and experience working with data will help you access this book more easily. |
| data analytics for digital marketing: Cutting-edge Marketing Analytics Rajkumar Venkatesan, Paul Farris, Ronald T. Wilcox, 2015 Master practical strategic marketing analysis through real-life case studies and hands-on examples. In Cutting Edge Marketing Analytics, three pioneering experts integrate all three core areas of marketing analytics: statistical analysis, experiments, and managerial intuition. They fully detail a best-practice marketing analytics methodology, augmenting it with case studies that illustrate the quantitative and data analysis tools you'll need to allocate resources, define optimal marketing mixes; perform effective analysis of customers and digital marketing campaigns, and create high-value dashboards and metrics. For each marketing problem, the authors help you: Identify the right data and analytics techniques Conduct the analysis and obtain insights from it Outline what-if scenarios and define optimal solutions Connect your insights to strategic decision-making Each chapter contains technical notes, statistical knowledge, case studies, and real data you can use to perform the analysis yourself. As you proceed, you'll gain an in-depth understanding of: The real value of marketing analytics How to integrate quantitative analysis with managerial sensibility How to apply linear regression, logistic regression, cluster analysis, and Anova models The crucial role of careful experimental design For all marketing professionals specializing in marketing analytics and/or business intelligence; and for students and faculty in all graduate-level business courses covering Marketing Analytics, Marketing Effectiveness, or Marketing Metrics |
| data analytics for digital marketing: Marketing Analytics Wayne L. Winston, 2014-01-08 Helping tech-savvy marketers and data analysts solve real-world business problems with Excel Using data-driven business analytics to understand customers and improve results is a great idea in theory, but in today's busy offices, marketers and analysts need simple, low-cost ways to process and make the most of all that data. This expert book offers the perfect solution. Written by data analysis expert Wayne L. Winston, this practical resource shows you how to tap a simple and cost-effective tool, Microsoft Excel, to solve specific business problems using powerful analytic techniques—and achieve optimum results. Practical exercises in each chapter help you apply and reinforce techniques as you learn. Shows you how to perform sophisticated business analyses using the cost-effective and widely available Microsoft Excel instead of expensive, proprietary analytical tools Reveals how to target and retain profitable customers and avoid high-risk customers Helps you forecast sales and improve response rates for marketing campaigns Explores how to optimize price points for products and services, optimize store layouts, and improve online advertising Covers social media, viral marketing, and how to exploit both effectively Improve your marketing results with Microsoft Excel and the invaluable techniques and ideas in Marketing Analytics: Data-Driven Techniques with Microsoft Excel. |
| data analytics for digital marketing: Creating Value with Data Analytics in Marketing Peter C. Verhoef, Edwin Kooge, Natasha Walk, Jaap E. Wieringa, 2021-11-07 The key competing texts are practitioner-focused ‘how to’ guides, whilst our book combines rigorous theory with practical insight and examples, with authors from both the academic and business world, making it more adoptable as a student text; Unlike other books on the subject, this has a customer focus and an exploration of how big data can add value to customers as well as organisations; Enables readers to move from big data to big solutions by demonstrating how to integrate data analytics into specific goals and processes for implementation; Highly successful and well regarded both for students and practitioners |
| data analytics for digital marketing: Data Science for Marketing Analytics Tommy Blanchard, Debasish Behera, Pranshu Bhatnagar, 2019-03-30 Explore new and more sophisticated tools that reduce your marketing analytics efforts and give you precise results Key FeaturesStudy new techniques for marketing analyticsExplore uses of machine learning to power your marketing analysesWork through each stage of data analytics with the help of multiple examples and exercisesBook Description Data Science for Marketing Analytics covers every stage of data analytics, from working with a raw dataset to segmenting a population and modeling different parts of the population based on the segments. The book starts by teaching you how to use Python libraries, such as pandas and Matplotlib, to read data from Python, manipulate it, and create plots, using both categorical and continuous variables. Then, you'll learn how to segment a population into groups and use different clustering techniques to evaluate customer segmentation. As you make your way through the chapters, you'll explore ways to evaluate and select the best segmentation approach, and go on to create a linear regression model on customer value data to predict lifetime value. In the concluding chapters, you'll gain an understanding of regression techniques and tools for evaluating regression models, and explore ways to predict customer choice using classification algorithms. Finally, you'll apply these techniques to create a churn model for modeling customer product choices. By the end of this book, you will be able to build your own marketing reporting and interactive dashboard solutions. What you will learnAnalyze and visualize data in Python using pandas and MatplotlibStudy clustering techniques, such as hierarchical and k-means clusteringCreate customer segments based on manipulated data Predict customer lifetime value using linear regressionUse classification algorithms to understand customer choiceOptimize classification algorithms to extract maximal informationWho this book is for Data Science for Marketing Analytics is designed for developers and marketing analysts looking to use new, more sophisticated tools in their marketing analytics efforts. It'll help if you have prior experience of coding in Python and knowledge of high school level mathematics. Some experience with databases, Excel, statistics, or Tableau is useful but not necessary. |
| data analytics for digital marketing: Creating Value with Big Data Analytics Peter C. Verhoef, Edwin Kooge, Natasha Walk, 2016-01-08 Our newly digital world is generating an almost unimaginable amount of data about all of us. Such a vast amount of data is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organisations to leverage the information to create value. This book is a refreshingly practical, yet theoretically sound roadmap to leveraging big data and analytics. Creating Value with Big Data Analytics provides a nuanced view of big data development, arguing that big data in itself is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. By tying data and analytics to specific goals and processes for implementation, this is a much-needed book that will be essential reading for students and specialists of data analytics, marketing research, and customer relationship management. |
| data analytics for digital marketing: Digital Marketing Analytics Kevin Hartman, 2020-09-15 From Kevin Hartman, Director of Analytics at Google, comes an essential guide for anyone seeking to collect, analyze, and visualize data in today's digital world (printed in brilliant full color). Even if you know nothing about digital marketing analytics, digital marketing analytics knows plenty about you. It's a fundamental, inescapable, and permanent cornerstone of modern business that affects the lives of analytics professionals and consumers in equal measure. This five-part book is an attempt to provide the context, perspective, and information needed to make analytics accessible to people who understand its reach and relevance and want to learn more. PART 1: The Day the Geeks Took Over The ubiquity of data analytics today isn't just a product of the past half-century's transformative and revolutionary changes in commerce and technology. Humanity has been developing, analyzing, and using data for millennia. Understanding where digital marketing analytics is now and where it will be in five, 10, or 50 years requires a holistic and historical view of our relationship and interaction with data. Part 1 looks at modern analysts and analytics in the context of its distinct historical epochs, each one containing major inflection points and laying a foundation for future advancements in the ART + SCIENCE that is modern data analytics. PART 2: Consumer/Brand Relationships The methods that brands use to build relationships with consumers - online video, search, display ads, and social media - give analysts a wealth of data about behaviors on these platforms. Knowing how to assess successful consumer/brand relationships and understanding a consumer's purchase journey requires a useable framework for parsing this data. In Part 2, we explore each digital channel in-depth, including a discussion of key metrics and measurements, how consumers interact with brands on each platform, and ways of organizing consumer data that enable actionable insights. PART 3: The Science of Analytics Part 3 focuses on understanding digital data creation, how brands use that data to measure digital marketing effectiveness, and the tools and skill sets analysts need to work effectively with data. While the contents are lightly technical, this section veers into the colloquial as we dive into multitouch attribution models, media mix models, incrementality studies, and other ways analysts conduct marketing measurement today. Part 3 also provides a useful framework for evaluating data analysis and visualization tools and explains the critical importance of digital marketing maturity to analysts and the companies for which they work. PART 4: The Art of Analytics Every analyst dreams of coming up with the Big Idea - the game-changing and previously unseen insight or approach that gives their organization a competitive advantage and their career a huge boost. But dreaming won't get you there. It requires a thoughtful and disciplined approach to analysis projects. In this part of the book, I detail the four elements of the Marketing Analytics Process (MAP): plan, collect, analyze, report. Part 4 also explains the role of the analyst, the six mutually exclusive and collectively exhaustive (MECE) marketing objectives, how to find context and patterns in collected data, and how to avoid the pitfalls of bias. PART 5: Storytelling with Data In Part 5, we dive headlong into the most important aspect of digital marketing analytics: transforming the data the analyst compiled into a comprehensive, coherent, and meaningful report. I outline the key characteristics of good visuals and the minutiae of chart design and provide a five-step process for analysts to follow when they're on their feet and presenting to an audience. |
| data analytics for digital marketing: Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing Singh, Amandeep, 2021-06-18 The availability of big data, low-cost commodity hardware, and new information management and analytic software have produced a unique moment in the history of data analysis. The convergence of these trends means that we have the capabilities required to analyze astonishing data sets quickly and cost-effectively for the first time in history. They represent a genuine leap forward and a clear opportunity to realize enormous gains in terms of efficiency, productivity, revenue, and profitability especially in digital marketing. Data plays a huge role in understanding valuable insights about target demographics and customer preferences. From every interaction with technology, regardless of whether it is active or passive, we are creating new data that can describe us. If analyzed correctly, these data points can explain a lot about our behavior, personalities, and life events. Companies can leverage these insights for product improvements, business strategy, and marketing campaigns to cater to the target customers. Big Data Analytics for Improved Accuracy, Efficiency, and Decision Making in Digital Marketing aids understanding of big data in terms of digital marketing for meaningful analysis of information that can improve marketing efforts and strategies using the latest digital techniques. The chapters cover a wide array of essential marketing topics and techniques, including search engine marketing, consumer behavior, social media marketing, online advertising, and how they interact with big data. This book is essential for professionals and researchers working in the field of analytics, data, and digital marketing, along with marketers, advertisers, brand managers, social media specialists, managers, sales professionals, practitioners, researchers, academicians, and students looking for the latest information on how big data is being used in digital marketing strategies. |
| data analytics for digital marketing: Cult of Analytics Steve Jackson, 2015-12-22 Cult of Analytics enables professionals to build an analytics driven culture into their business or organization. Marketers will learn how to turn tried and tested tactics into an actionable plan to change their culture to one that uses web analytics on a day to day basis. Through use of the fictitious ACME PLC case, Steve Jackson provides working examples based on real life situations from the various companies he has worked with, such as Nokia, KONE, Rovio, Amazon, Expert, IKEA, Vodafone, and EMC. These examples will give the reader practical techniques for their own business regardless of size or situation making Cult of Analytics a must have for any would-be digital marketer. This new edition has been thoroughly updated, now including examples out of how to get the best from Google analytics, as well as ways to use social media data, big data, tag management and advanced persona segmentation to drive real value in your organisation. It's also been expanded to include exercises and new cases for students and tutors using the book as a text. |
| data analytics for digital marketing: Marketing Strategy Robert W. Palmatier, Shrihari Sridhar, 2020-12-31 Marketing Strategy offers a unique and dynamic approach based on four underlying principles that underpin marketing today: All customers differ; All customers change; All competitors react; and All resources are limited. The structured framework of this acclaimed textbook allows marketers to develop effective and flexible strategies to deal with diverse marketing problems under varying circumstances. Uniquely integrating marketing analytics and data driven techniques with fundamental strategic pillars the book exemplifies a contemporary, evidence-based approach. This base toolkit will support students' decision-making processes and equip them for a world driven by big data. The second edition builds on the first's successful core foundation, with additional pedagogy and key updates. Research-based, action-oriented, and authored by world-leading experts, Marketing Strategy is the ideal resource for advanced undergraduate, MBA, and EMBA students of marketing, and executives looking to bring a more systematic approach to corporate marketing strategies. New to this Edition: - Revised and updated throughout to reflect new research and industry developments, including expanded coverage of digital marketing, influencer marketing and social media strategies - Enhanced pedagogy including new Worked Examples of Data Analytics Techniques and unsolved Analytics Driven Case Exercises, to offer students hands-on practice of data manipulation as well as classroom activities to stimulate peer-to-peer discussion - Expanded range of examples to cover over 250 diverse companies from 25 countries and most industry segments - Vibrant visual presentation with a new full colour design |
| data analytics for digital marketing: Data-First Marketing Janet Driscoll Miller, Julia Lim, 2020-08-21 Supercharge your marketing strategy with data analytics In Data-First Marketing: How to Compete & Win in the Age of Analytics, distinguished authors Miller and Lim demystify the application of data analytics to marketing in any size business. Digital transformation has created a widening gap between what the CEO and business expect marketing to do and what the CMO and the marketing organization actually deliver. The key to unlocking the true value of marketing is data – from actual buyer behavior to targeting info on social media platforms to marketing’s own campaign metrics. Data is the next big battlefield for not just marketers, but also for the business because the judicious application of data analytics will create competitive advantage in the Age of Analytics. Miller and Lim show marketers where to start by leveraging their decades of experience to lay out a step-by-step process to help businesses transform into data-first marketing organizations. The book includes a self-assessment which will help to place your organization on the Data-First Marketing Maturity Model and serve as a guide for which steps you might need to focus on to complete your own transformation. Data-First Marketing: How to Compete & Win in the Age of Analytics should be used by CMOs and heads of marketing to institute a data-first approach throughout the marketing organization. Marketing staffers can pick up practical tips for incorporating data in their daily tasks using the Data-First Marketing Campaign Framework. And CEOs or anyone in the C-suite can use this book to see what is possible and then help their marketing teams to use data analytics to increase pipeline, revenue, customer loyalty – anything that drives business growth. |
| data analytics for digital marketing: Marketing Analytics Mike Grigsby, 2018-04-03 Who is most likely to buy and what is the best way to target them? How can businesses improve strategy without identifying the key influencing factors? The second edition of Marketing Analytics enables marketers and business analysts to leverage predictive techniques to measure and improve marketing performance. By exploring real-world marketing challenges, it provides clear, jargon-free explanations on how to apply different analytical models for each purpose. From targeted list creation and data segmentation, to testing campaign effectiveness, pricing structures and forecasting demand, this book offers a welcome handbook on how statistics, consumer analytics and modelling can be put to optimal use. The fully revised second edition of Marketing Analytics includes three new chapters on big data analytics, insights and panel regression, including how to collect, separate and analyze big data. All of the advanced tools and techniques for predictive analytics have been updated, translating models such as tobit analysis for customer lifetime value into everyday use. Whether an experienced practitioner or having no prior knowledge, methodologies are simplified to ensure the more complex aspects of data and analytics are fully accessible for any level of application. Complete with downloadable data sets and test bank resources, this book supplies a concrete foundation to optimize marketing analytics for day-to-day business advantage. |
| data analytics for digital marketing: Big Data Analytics Kiran Chaudhary, Mansaf Alam, 2022-01-19 Big Data Analytics: Applications in Business and Marketing explores the concepts and applications related to marketing and business as well as future research directions. It also examines how this emerging field could be extended to performance management and decision-making. Investment in business and marketing analytics can create value through proper allocation of resources and resource orchestration process. The use of data analytics tools can be used to diagnose and improve performance. The book is divided into five parts. The first part introduces data science, big data, and data analytics. The second part focuses on applications of business analytics including: Big data analytics and algorithm Market basket analysis Anticipating consumer purchase behavior Variation in shopping patterns Big data analytics for market intelligence The third part looks at business intelligence and features an evaluation study of churn prediction models for business Intelligence. The fourth part of the book examines analytics for marketing decision-making and the roles of big data analytics for market intelligence and of consumer behavior. The book concludes with digital marketing, marketing by consumer analytics, web analytics for digital marketing, and smart retailing. This book covers the concepts, applications and research trends of marketing and business analytics with the aim of helping organizations increase profitability by improving decision-making through data analytics. |
| data analytics for digital marketing: Contemporary Issues in Digital Marketing Outi Niininen, 2021-11-29 This book presents a comprehensive overview of the key topics, best practices, future opportunities and challenges in the Digital Marketing discourse. With contributions from world-renowned experts, the book covers: Big Data, Artificial Intelligence and Analytics in Digital Marketing Emerging technologies and how they can enhance User Experience How ‘digital’ is changing servicescapes Issues surrounding ethics and privacy Current and future issues surrounding Social Media Key considerations for the future of Digital Marketing Case studies and examples from real-life organisations Unique in its rigorous, research-driven and accessible approach to the subject of Digital Marketing, this text is valuable supplementary reading for advanced undergraduate and postgraduate students studying Digital and Social Media Marketing, Customer Experience Management, Digital Analytics and Digital Transformation. |
| data analytics for digital marketing: Building a Digital Analytics Organization Judah Phillips, 2013-07-25 Drive maximum business value from digital analytics, web analytics, site analytics, and business intelligence! In Building a Digital Analytics Organization, pioneering expert Judah Phillips thoroughly explains digital analytics to business practitioners, and presents best practices for using it to reduce costs and increase profitable revenue throughout the business. Phillips covers everything from making the business case through defining and executing strategy, and shows how to successfully integrate analytical processes, technology, and people in all aspects of operations. This unbiased and product-independent guide is replete with examples, many based on the author’s own extensive experience. Coverage includes: key concepts; focusing initiatives and strategy on business value, not technology; building an effective analytics organization; choosing the right tools (and understanding their limitations); creating processes and managing data; analyzing paid, owned, and earned digital media; performing competitive and qualitative analyses; optimizing and testing sites; implementing integrated multichannel digital analytics; targeting consumers; automating marketing processes; and preparing for the revolutionary “analytical economy.” For all business practitioners interested in analytics and business intelligence in all areas of the organization. |
| data analytics for digital marketing: Digital Analytics for Marketing Gohar F. Khan, Marshall Sponder, 2017-10-05 This comprehensive book provides students with a grand tour of the tools needed to measure digital activity and implement best practices for using data to inform marketing strategy. It is the first text of its kind to introduce students to analytics platforms from a practical marketing perspective. Demonstrating how to integrate large amounts of data from web, digital, social, and search platforms, this helpful guide offers actionable insights into data analysis, explaining how to connect the dots and humanize information to make effective marketing decisions. The author covers timely topics, such as social media, web analytics, marketing analytics challenges, and dashboards, helping students to make sense of business measurement challenges, extract insights, and take effective actions. The book’s experiential approach, combined with chapter objectives, summaries, and review questions, will engage readers, deepening learning by helping them to think outside the box. Filled with engaging, interactive exercises, and interesting insights from an industry expert, this book will appeal to students of digital marketing, online marketing, and analytics. A companion website features an instructor’s manual, test bank, and PowerPoint slides. |
| data analytics for digital marketing: Marketing and Sales Analytics Cesar A. Brea, 2014 Today, an effective marketing analytics executive is even more important than a brilliant data scientist. That's because successful analytics investments now require managerial orchestration of many elements that go far beyond conventional definitions of analytics. Marketing and Sales Analytics examines the experiences of sales and marketing leaders and practitioners who have successfully built high value analytics capabilities in multiple industries. Then, drawing on their experiences, top analytics consultant Cesar Brea introduces overarching frameworks and specific tools that can help you achieve the same levels of success in your own organization. Brea shows how to: Establish the ecosystemic conditions for analytic success Reconcile the diverse perspectives that impact analytics initiatives (Business v. IT, Sales v. Marketing, Analysts v. Creatives v. Managers, and Everyone v. Finance) Decide what success will look like Agree on the questions to ask Organize both internal and external data Establish operational flexibility, and balance flexibility with efficiency Recruit the right people and organize them optimally Intelligently decide what to do yourself, and what to hire vendors for Balance research, analytics, and testing Implement proven research, analytics, and testing strategies Deliver results through storytelling (and recognize its limitations) Control the biases that creep into analytics research Maintain momentum, implement governance, and keep score |
| data analytics for digital marketing: Predictive Marketing Omer Artun, Dominique Levin, 2015-08-06 Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience. |
| data analytics for digital marketing: Social Media Marketing Ajit V. Jaokar, Brian Jacobs, Alan Moore, 2009-02 Providing an understanding of the world of social media from the perspective of the Web, this resource presents case studies from enterprises that have successfully used the social media marketing approach. |
| data analytics for digital marketing: Web Analytics Avinash Kaushik, 2007-07-30 Written by an in-the-trenches practitioner, this step-by-step guide shows you how to implement a successful Web analytics strategy. Web analytics expert Avinash Kaushik, in his thought-provoking style, debunks leading myths and leads you on a path to gaining actionable insights from your analytics efforts. Discover how to move beyond clickstream analysis, why qualitative data should be your focus, and more insights and techniques that will help you develop a customer-centric mindset without sacrificing your company’s bottom line. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| data analytics for digital marketing: Principles of Marketing Engineering, 2nd Edition Gary L. Lilien, Arvind Rangaswamy, Arnaud De Bruyn, 2013 The 21st century business environment demands more analysis and rigor in marketing decision making. Increasingly, marketing decision making resembles design engineering-putting together concepts, data, analyses, and simulations to learn about the marketplace and to design effective marketing plans. While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems). Marketing Engineering is the systematic approach to harness data and knowledge to drive effective marketing decision making and implementation through a technology-enabled and model-supported decision process. (For more information on Excel-based models that support these concepts, visit DecisionPro.biz.) We have designed this book primarily for the business school student or marketing manager, who, with minimal background and technical training, must understand and employ the basic tools and models associated with Marketing Engineering. We offer an accessible overview of the most widely used marketing engineering concepts and tools and show how they drive the collection of the right data and information to perform the right analyses to make better marketing plans, better product designs, and better marketing decisions. What's New In the 2nd Edition While much has changed in the nearly five years since the first edition of Principles of Marketing Engineering was published, much has remained the same. Hence, we have not changed the basic structure or contents of the book. We have, however Updated the examples and references. Added new content on customer lifetime value and customer valuation methods. Added several new pricing models. Added new material on reverse perceptual mapping to describe some exciting enhancements to our Marketing Engineering for Excel software. Provided some new perspectives on the future of Marketing Engineering. Provided better alignment between the content of the text and both the software and cases available with Marketing Engineering for Excel 2.0. |
| data analytics for digital marketing: Marketing Analytics: A Practitioner's Guide To Marketing Analytics And Research Methods Ashok Charan, 2015-05-20 The digital age has transformed the very nature of marketing. Armed with smartphones, tablets, PCs and smart TVs, consumers are increasingly hanging out on the internet. Cyberspace has changed the way they communicate, and the way they shop and buy. This fluid, de-centralized and multidirectional medium is changing the way brands engage with consumers.At the same time, technology and innovation, coupled with the explosion of business data, has fundamentally altered the manner we collect, process, analyse and disseminate market intelligence. The increased volume, variety and velocity of information enables marketers to respond with much greater speed, to changes in the marketplace. Market intelligence is timelier, less expensive, and more accurate and actionable.Anchored in this age of transformations, Marketing Analytics is a practitioner's guide to marketing management in the 21st century. The text devotes considerable attention to the way market analytic techniques and market research processes are being refined and re-engineered. Written by a marketing veteran, it is intended to guide marketers as they craft market strategies, and execute their day to day tasks. |
| data analytics for digital marketing: Creating Value with Data Analytics in Marketing Peter C. Verhoef, Edwin Kooge, Natasha Walk, Jaap E. Wieringa, 2021-11-07 This book is a refreshingly practical yet theoretically sound roadmap to leveraging data analytics and data science. The vast amount of data generated about us and our world is useless without plans and strategies that are designed to cope with its size and complexity, and which enable organizations to leverage the information to create value in marketing. Creating Value with Data Analytics in Marketing provides a nuanced view of big data developments and data science, arguing that big data is not a revolution but an evolution of the increasing availability of data that has been observed in recent times. Building on the authors’ extensive academic and practical knowledge, this book aims to provide managers and analysts with strategic directions and practical analytical solutions on how to create value from existing and new big data. The second edition of this bestselling text has been fully updated in line with developments in the field and includes a selection of new, international cases and examples, exercises, techniques and methodologies. Tying data and analytics to specific goals and processes for implementation makes this essential reading for advanced undergraduate and postgraduate students and specialists of data analytics, marketing research, marketing management and customer relationship management. Online resources include chapter-by-chapter lecture slides and data sets and corresponding R code for selected chapters. |
| data analytics for digital marketing: Hands-On Data Science for Marketing Yoon Hyup Hwang, 2019-03-29 Optimize your marketing strategies through analytics and machine learning Key FeaturesUnderstand how data science drives successful marketing campaignsUse machine learning for better customer engagement, retention, and product recommendationsExtract insights from your data to optimize marketing strategies and increase profitabilityBook Description Regardless of company size, the adoption of data science and machine learning for marketing has been rising in the industry. With this book, you will learn to implement data science techniques to understand the drivers behind the successes and failures of marketing campaigns. This book is a comprehensive guide to help you understand and predict customer behaviors and create more effectively targeted and personalized marketing strategies. This is a practical guide to performing simple-to-advanced tasks, to extract hidden insights from the data and use them to make smart business decisions. You will understand what drives sales and increases customer engagements for your products. You will learn to implement machine learning to forecast which customers are more likely to engage with the products and have high lifetime value. This book will also show you how to use machine learning techniques to understand different customer segments and recommend the right products for each customer. Apart from learning to gain insights into consumer behavior using exploratory analysis, you will also learn the concept of A/B testing and implement it using Python and R. By the end of this book, you will be experienced enough with various data science and machine learning techniques to run and manage successful marketing campaigns for your business. What you will learnLearn how to compute and visualize marketing KPIs in Python and RMaster what drives successful marketing campaigns with data scienceUse machine learning to predict customer engagement and lifetime valueMake product recommendations that customers are most likely to buyLearn how to use A/B testing for better marketing decision makingImplement machine learning to understand different customer segmentsWho this book is for If you are a marketing professional, data scientist, engineer, or a student keen to learn how to apply data science to marketing, this book is what you need! It will be beneficial to have some basic knowledge of either Python or R to work through the examples. This book will also be beneficial for beginners as it covers basic-to-advanced data science concepts and applications in marketing with real-life examples. |
| data analytics for digital marketing: The Economics of Data, Analytics, and Digital Transformation Bill Schmarzo, Dr. Kirk Borne, 2020-11-30 Build a continuously learning and adapting organization that can extract increasing levels of business, customer and operational value from the amalgamation of data and advanced analytics such as AI and Machine Learning Key Features Master the Big Data Business Model Maturity Index methodology to transition to a value-driven organizational mindset Acquire implementable knowledge on digital transformation through 8 practical laws Explore the economics behind digital assets (data and analytics) that appreciate in value when constructed and deployed correctly Book Description In today's digital era, every organization has data, but just possessing enormous amounts of data is not a sufficient market discriminator. The Economics of Data, Analytics, and Digital Transformation aims to provide actionable insights into the real market discriminators, including an organization's data-fueled analytics products that inspire innovation, deliver insights, help make practical decisions, generate value, and produce mission success for the enterprise. The book begins by first building your mindset to be value-driven and introducing the Big Data Business Model Maturity Index, its maturity index phases, and how to navigate the index. You will explore value engineering, where you will learn how to identify key business initiatives, stakeholders, advanced analytics, data sources, and instrumentation strategies that are essential to data science success. The book will help you accelerate and optimize your company's operations through AI and machine learning. By the end of the book, you will have the tools and techniques to drive your organization's digital transformation. Here are a few words from Dr. Kirk Borne, Data Scientist and Executive Advisor at Booz Allen Hamilton, about the book: Data analytics should first and foremost be about action and value. Consequently, the great value of this book is that it seeks to be actionable. It offers a dynamic progression of purpose-driven ignition points that you can act upon. What you will learn Train your organization to transition from being data-driven to being value-driven Navigate and master the big data business model maturity index Learn a methodology for determining the economic value of your data and analytics Understand how AI and machine learning can create analytics assets that appreciate in value the more that they are used Become aware of digital transformation misconceptions and pitfalls Create empowered and dynamic teams that fuel your organization's digital transformation Who this book is for This book is designed to benefit everyone from students who aspire to study the economic fundamentals behind data and digital transformation to established business leaders and professionals who want to learn how to leverage data and analytics to accelerate their business careers. |
| data analytics for digital marketing: Social Media Analytics Strategy Alex Gonçalves, 2017-11-12 This book shows you how to use social media analytics to optimize your business performance. The tools discussed will prepare you to create and implement an effective digital marketing strategy. From understanding the data and its sources to detailed metrics, dashboards, and reports, this book is a robust tool for anyone seeking a tangible return on investment from social media and digital marketing. Social Media Analytics Strategy speaks to marketers who do not have a technical background and creates a bridge into the digital world. Comparable books are either too technical for marketers (aimed at software developers) or too basic and do not take strategy into account. They also lack an overview of the entire process around using analytics within a company project. They don’t go into the everyday details and also don’t touch upon common mistakes made by marketers. This book highlights patterns of common challenges experienced by marketers from entry level to directors and C-level executives. Social media analytics are explored and explained using real-world examples and interviews with experienced professionals and founders of social media analytics companies. What You’ll Learn Get a clear view of the available data for social media marketing and how to access all of it Make use of data and information behind social media networks to your favor Know the details of social media analytics tools and platforms so you can use any tool in the market Apply social media analytics to many different real-world use cases Obtain tips from interviews with professional marketers and founders of social media analytics platforms Understand where social media is heading, and what to expect in the future Who This Book Is For Marketing professionals, social media marketing specialists, analysts up to directors and C-level executives, marketing students, and teachers of social media analytics/social media marketing |
| data analytics for digital marketing: Digital Marketing Analytics Chuck Hemann, Ken Burbary, 2018-04-23 Distill Maximum Value from Your Digital Data! Do It Now! Why hasn’t all that data delivered a whopping competitive advantage? Because you’ve barely begun to use it, that’s why! Good news: neither have your competitors. It’s hard! But digital marketing analytics is 100% doable, it offers colossal opportunities, and all of the data is accessible to you. Chuck Hemann and Ken Burbary will help you chop the problem down to size, solve every piece of the puzzle, and integrate a virtually frictionless system for moving from data to decision, action to results! Scope it out, pick your tools, learn to listen, get the metrics right, and then distill your digital data for maximum value for everything from R&D to customer service to social media marketing! Prioritize—because you can’t measure and analyze everything Use analysis to craft experiences that profoundly reflect each customer’s needs, expectations, and behaviors Measure real digital media ROI: sales, leads, and customer satisfaction Track the performance of all paid, earned, and owned digital channels Leverage digital data way beyond PR and marketing: for strategic planning, product development, and HR Start optimizing digital content in real time Implement advanced tools, processes, and algorithms for accurately measuring influence Make the most of surveys, focus groups, and offline research synergies Focus new marketing investments where they’ll deliver the most value • Identify and understand your most important audiences across the digital ecosystem “Chuck and Ken lead marketers clearly and efficiently through the minefield of digital marketing measurement. And they do so with a lightness of touch and absence of jargon so rare in this overhyped, much-misunderstood ecosystem.” — Sam Knowles, Founder & MD of Insight Agents; author of Narrative by Numbers: How to Tell Powerful & Purposeful Stories with Data |
| data analytics for digital marketing: Sport Business Analytics C. Keith Harrison, Scott Bukstein, 2016-11-18 Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group. The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in: Ticket pricing Season ticket member retention Fan engagement Sponsorship valuation Customer relationship management Digital marketing Market research Data visualization. This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations. Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics. |
| data analytics for digital marketing: Performance Marketing with Google Analytics Sebastian Tonkin, Caleb Whitmore, Justin Cutroni, 2011-01-21 An unparalleled author trio shares valuable advice for using Google Analytics to achieve your business goals Google Analytics is a free tool used by millions of Web site owners across the globe to track how visitors interact with their Web sites, where they arrive from, and which visitors drive the most revenue and sales leads. This book offers clear explanations of practical applications drawn from the real world. The author trio of Google Analytics veterans starts with a broad explanation of performance marketing and gets progressively more specific, closing with step-by-step analysis and applications. Features in-depth examples and case studies on how to increase revenue from search advertising, optimize an existing website, prioritize channels and campaigns, access brand health and more Discusses how to communicate with a webmaster or developer to assist with installation Addresses Google's conversion-oriented tools, including AdWords and AdSense, Google trends, Webmaster tools, search-based keyword tools, and more Touches on brand tracking studies, usability research, competitive analysis, and statistical tools Throughout the book, the main emphasis is demonstrating how you can best use Google Analytics to achieve your business objectives. Foreword by Avinash Kaushik Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file. |
| data analytics for digital marketing: Digital Marketing Strategy Simon Kingsnorth, 2016-05-03 The modern marketer needs to learn how to employ strategic thinking alongside the use of digital media to deliver measurable and accountable business success. Digital Marketing Strategy covers the essential elements of achieving exactly this by guiding you through every step of creating your perfect digital marketing strategy. This book analyzes the essential techniques and platforms of digital marketing including social media, content marketing, SEO, user experience, personalization, display advertising and CRM, as well as the broader aspects of implementation including planning, integration with overall company aims and presenting to decision makers. Simon Kingsnorth brings digital marketing strategy to life through best practice case studies, illustrations, checklists and summaries, to give you insightful and practical guidance. Rather than presenting a restrictive 'one size fits all' model, this book gives you the tools to tailor-make your own strategy according to your unique business needs and demonstrates how an integrated and holistic approach to marketing leads to greater success. Digital Marketing Strategy is also supported by a wealth of online resources, including budget and strategy templates, lecture slides and a bonus chapter. |
| data analytics for digital marketing: Marketing Analytics Robert W. Palmatier, J. Andrew Petersen, Frank Germann, 2022-03-24 Using data analytics and big data in marketing and strategic decision-making is a key priority at many organisations and subsequently a vital part of the skills set for a successful marketing professional operating today. Authored by world-leading authorities in the field, Marketing Analytics provides a thoroughly contemporary overview of marketing analytics and coverage of a wide range of cutting edge data analytics techniques. It offers a powerful framework, organising data analysis techniques around solving four underlying marketing problems: the 'First Principles of Marketing'. In this way, it offers an action-oriented, applied approach to managing marketing complexities and issues, and a sound grounding in making effective decisions based on strong evidence. It is supported by vivid international cases and examples, and applied pedagogical features. The companion website offers comprehensive classroom instruction slides, videos including walk throughs on all the examples and methods in the book, data sets, a test bank and a solution guide for instructors. |
| data analytics for digital marketing: Tap Anindya Ghose, 2017-04-14 How the smartphone can become a personal concierge (not a stalker) in the mobile marketing revolution of smarter companies, value-seeking consumers, and curated offers. Consumers create a data trail by tapping their phones; businesses can tap into this trail to harness the power of the more than three trillion dollar mobile economy. According to Anindya Ghose, a global authority on the mobile economy, this two-way exchange can benefit both customers and businesses. In Tap, Ghose welcomes us to the mobile economy of smartphones, smarter companies, and value-seeking consumers. Drawing on his extensive research in the United States, Europe, and Asia, and on a variety of real-world examples from companies including Alibaba, China Mobile, Coke, Facebook, SK Telecom, Telefónica, and Travelocity, Ghose describes some intriguingly contradictory consumer behavior: people seek spontaneity, but they are predictable; they find advertising annoying, but they fear missing out; they value their privacy, but they increasingly use personal data as currency. When mobile advertising is done well, Ghose argues, the smartphone plays the role of a personal concierge—a butler, not a stalker. Ghose identifies nine forces that shape consumer behavior, including time, crowdedness, trajectory, and weather, and he examines these how these forces operate, separately and in combination. With Tap, he highlights the true influence mobile wields over shoppers, the behavioral and economic motivations behind that influence, and the lucrative opportunities it represents. In a world of artificial intelligence, augmented and virtual reality, wearable technologies, smart homes, and the Internet of Things, the future of the mobile economy seems limitless. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will enable a …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels to …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
